|Introduction||Image Enhancement||Particle Picking||Classification||Reconstruction||3D Image Segmentation||Secondary Structure||References||Acknowledgements|
Particle picking algorithm provides us a set of particles, each of which corresponds to one projection of the 3D particle structure. However, some of the particles may have roughly the same “appearance”, which means they differ from each other only under certain amount of in-plane rotation, translation and/or scaling. All particles with similar “appearance” can thus be aligned and averaged to obtain an averaged image that is supposed to have a much better signal-to-noise ratio. But before we do the alignment and averaging, we must classify all the particle images into different groups based upon their “appearance”. All such averaged images (one per class) are used as inputs to the Reconstruction. The following picture shows the pipeline of particle classification, alignment and averaging, starting from the detected particles and ending up with a set of particle averages.
Pipeline of particle classification.
Image classification is a well-studied topic in image processing. However, very few techniques on particle classification have been explored in single particle reconstruction. We intend to do something on this problem but we have not yet started.